All points histogram sweep formula operation

[timjarsky]

PSXPrep() creates an all-point histogram fit with a Gaussian. Create a similar operation that works independently of PSX and is more feature-rich.

AllPoints(data(), gaussian(), dblExp_peak(),diff(), GroupBy())

Gaussian() - Fit data with gaussian.
Lorenzian() - Fit the data with a lor.

diff = 0, plot histogram with both user-specified fit. (e.g., PSX prep()). No harm in plotting the SD at a particular value on the plot, like PSXprep does. e.g., diff(0, [SD]). default to SD = 3
diff = 1, plot histogram - Gaussian() (i.e., subtract the Gaussian fit from the all points histogram. Fit with dblExp_peak.
diff=3, plot a user-specified fit parameter from the dblExpPpeak() vs the peak voltage of the Gaussian fit

For Diff = 2, give the user the ability to constrain the voltage range over which the fit is made (e.g., diff(2, SD, [-55,-50]).

GroupBY([voltage/current Range]) default is group data by sweep. In the group by voltage/current mode, the data within a group is in the same voltage range (-50 +- 1 mV). For example, group all epochs where the mean voltage of the epoch is within +/- 1 mV. e.g., GroupBy(1). I think K-means clustering could work here.

We'll want to be able to fit the XY pairs generated by multiple sweeps/groups.

The goal is to capture how the fit parameters change as function of sweep or mean voltage(or current).

sample plot showing dblExp_peak() fit to the subtracted traces

When using store(), the store operation will store all the fit results for both fits and the all points histogram

[timjarsky]

Consider how to merge the data from different ranges - aligning them at the mean/median probably makes sense.

We want to be careful about mixing data/ranges with different mean/median voltages

Also want to check for drift in a trace - mean/median voltage should re relatively constant on a TBD timescale

Tentative order of operations:

1. check for drift in individual ranges. Only use ranges where drift is as specified by driftCheck(mean drift < 0.5 mV, movingavg method user-defined time window)
2. align all ranges by the mean/median align(mean)
3. all-points histogram across all ranges. Align peak at zero? How is bin size determined?
4. fit all points with gaussian, lorentzian, or gauss + double eponential. rank the fit quality?
5. return fit parameters